Numerous controls rely on authentication or identification based on biometric characteristics, for instance to allow an individual to access a secure place or to proceed with a secure transaction.
Some controls are implemented by recording a video of a biometric characteristic (e.g. iris) of an individual, and comparing the extracted biometric features to a database of recorded individuals to find a match.
To fool such a control, attacks have been developed in which an imposter uses a stolen biometric sample from a database to gain access to the secured zone or is allowed to perform the transaction.
These attacks (i.e. presentation attacks) can take the form of a print attack, in which a biometric sample is printed using high quality laserjet or inkjet printer, and used during the control process. Therefore during the control, a video of the print, instead of the genuine biometric characteristic, is recorded.
Attacks can also take the form of a replay video attack, in which a high quality electronic video displaying a biometric sample is used during the control process. In that case, the control system records a new video of the displayed video instead of the biometric characteristic.
A control system should be able to detect such presentation attacks in order to be secure and reliable, and thus should be able to determine the liveness of the subject of the recording (either a genuine biometric characteristic, or a replay video, or a print of the biometric sample).
A process for detecting presentation attacks on face recognition capture devices has been proposed in the document of S. Bharadwaj, T. I. Dhamecha, M. Vatsa and R. Singh, Computationally efficient face spoofing detection with motion magnification, in 2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops, pages 105-110, IEEE, 2013.
This process relies on using magnitude of motion magnification and texture descriptors, and is therefore not adapted for other kinds of biometric characteristics such as, for instance, irises that are relied upon on replay video attacks.
Therefore there is a need for a process allowing detection of replay video attacks in iris recognition.